Abstract
In order to understand and explain IT-related organizational change, information systems researchers have adopted several practice-oriented theories from sociology, and science and
technology studies. These “grand theories” are often complex and operate on a high level of abstraction, thus, making them suitable for collecting rich process data while following multifaceted empirical phenomena over time. As a consequence, it may be challenging to organize and analyse the abundant process data in order to create a foundation for theory building, while also being loyal to the “grand theory” as well as to the logic of process research. The purpose of this paper is to propose a systematic approach in order to facilitate this “intermediate step” of sensemaking between data collection and theory building. The suggested approach comprises three interrelated and iterative processes for organizing and analysing process data in order to build a foundation for theorizing: process data are chronologically organized and a thick case history is written; the case history is interpreted as a narrative informed by the “grand theory” and coded as events; chains of events are bracketed together and graphically represented in terms of episodes, separated by critical events that challenge the path forward. In this way, comparable units of analysis are created facilitating the analysis of patterns within and among episode, as well as the identification of underlying
mechanisms. By making explicit the “intermediate step”, the approach bridges the gap between data collection and theory building in a way that is substantiated by empirical data, the “grand theory”, and the logic of process research. The paper demonstrates how the approach can be employed by examples from an in-depth longitudinal case study.